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a. Computerized Numerical Control (CNC)
Together with PLC, CNC comprises the machine's control system, where we find all the variables and parameters related to the process and its control. Due to the importance of the data that can be extracted, Aingura IIoT has connectivity modules that make it possible to obtain this data, including (if necessary) bidirectional capacity to develop optimum interaction with the machine. All of this is accomplished without influencing the machine's functional cycle.
Aingura IIoT also enables connectivity with sensors in different domains. They can be included within the communication bus of the machine (or not), making it a highly useful characteristic in legacy versions.
As for the type of sensors, there are practically no limits, as long as they provide readable signals. They include the following types: vibration; energy consumption (electricity, air, fluids); temperature; pressure; flow; position; particles; and humidity, amongst others.
c. Sensor Fusion
With sensor fusion, Aingura IIoT has the capacity to integrate data coming from different domains, for example, PLC/CNC and external sensors. This makes it possible to enrich them with precision, ensuring the quality of the data to be later used to deliver relevant information related both to the machine and the prime material employed.
By crossing data between PLC/CNC and sensors, Aingura IIoT enables analysis of the main agent in the process, as is the case with the mechanizing tool where work is done. It does this by extracting relevant information on its state, useful life and performance, amongst other factors. All this is made possible through real-time analysis of the data coming from the machine.
e. Work product
Thanks to the ongoing monitoring of the process and the crossing of data related to it, Aingura IIoT makes it possible to observe variations in the raw material of the piece and in its quality. This is feasible through the analysis of behavior patterns drawn from historical data.
This is the interaction interface with the operator, where it is possible for Aingura IIoT to deliver all necessary information to assist in achieving maximum performance. Interaction here is bidirectional, so that different operational parameters used by the operator can be considered, delivering insights of their effect and thus helping to refine the machine's optimal operational setting.
Aingura IIoT's advanced data analysis brings competitive advantage for diagnostic needs, prognosis requirements and knowledge discovery. In this way it improves machine performance, future machine behavior and the creation of new production scenarios by historical exploration. Aingura IIoT develops highly efficient, specifically-tailored, machine-learning algorithms working with data streams, not relying on heavy databases.
Aingura IIoT Node works at the edge, carrying out data acquisition, pre-processing and processing.
Acquisition: Aingura IIoT acquires data from different domains using OPC-UA or DDS-Secure industrial and other IIoT protocols over networks like TSN (Time Sensitive Network), for Deterministic communications over Ethernet.
Pre-processing: Filtering and sensor fusion tasks are carried out to ensure data quality.
Processing: Aingura IIoT uses specifically-tailored, machine-learning algorithms to solve a variety of relevant queries in generating useful information for decision making, ensuring excellent performance and delivering a response in the required time frame. To do so, it is vital to have greater computing capacity. Aingura IIoT uses high-performance computing technologies taking advantage of high availability, distributed and parallel computation.
Aingura IIoT makes it possible to optimize energy consumption of productive resources by actively detecting and controlling the principal consumers in the system. The resultant saving can represent a return on the investment made in implementing this solution.
As a tool to ensure optimal performance and the delivery of a response in the set time frame, the application of complex calculation could be necessary, making greater computing capacity essential. For this reason, Aingura HPC (US patent pending 2017) takes full advantage of the available resources in other nodes to perform computing that is available, distributed and parallel to a high degree.
In this way, when dealing with cloud Aingura HPC makes it possible to ensure viable processing costs in industrial environments, with a solution that is less costly, more secure and more robust. This viability, when comparing with a cloud service, is even further enhanced to the degree that significant bandwidth requirements are ruled out, along with costly communication infrastructures and services managed by third parties making internal information more expensive while exposing it to greater security risk.
Aingura IIoT Solution Master node does part of the architecture at the edge of Aingura HPC (US patent pending 2017), taking advantage of available resources in other nodes to perform computing that is available, distributed and parallel to a high degree. This node does administrative tasks, fielding queries and distributing tasks to every Aingura IIoT Solution Node with available resources. Furthermore, it carries out other setting-related tasks as part of the maintenance of the HPC infrastructure.
Requires information from the edge for decision-making related to the line's maintenance and availability. Aingura IIoT Solution enables the Production Line Manager to obtain actionable insights at the right time.
It's responsible for the competitive analysis of the plant and is concerned with reducing per piece energy consumption. Aingura IIoT enables the Manufacturing Plant Manager to make decisions related to production increases using delivered information. In this way, Aingura IIoT can be set to automatically or manually assist in decision-making.